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requirements_lock_3_12.txt
tblib==2.0.0 \ --hash=sha256:9100bfa016b047d5b980d66e7efed952fbd20bd85b56110aaf473cb97d18709a \ --hash=sha256:a6df30f272c08bf8be66e0775fad862005d950a6b8449b94f7c788731d70ecd7 # via -r requirements.in tensorboard-data-server==0.7.2 \ --hash=sha256:7e0610d205889588983836ec05dc098e80f97b7e7bbff7e994ebb78f578d0ddb \ --hash=sha256:9fe5d24221b29625dbc7328b0436ca7fc1c23de4acf4d272f1180856e32f9f60 \
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requirements_lock_3_9.txt
tblib==2.0.0 \ --hash=sha256:9100bfa016b047d5b980d66e7efed952fbd20bd85b56110aaf473cb97d18709a \ --hash=sha256:a6df30f272c08bf8be66e0775fad862005d950a6b8449b94f7c788731d70ecd7 # via -r requirements.in tensorboard-data-server==0.7.2 \ --hash=sha256:7e0610d205889588983836ec05dc098e80f97b7e7bbff7e994ebb78f578d0ddb \ --hash=sha256:9fe5d24221b29625dbc7328b0436ca7fc1c23de4acf4d272f1180856e32f9f60 \
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tensorflow/c/c_api_experimental.cc
TF_CheckpointReader* reader = new TF_CheckpointReader(filename, status); if (!status->status.ok()) { TF_DeleteCheckpointReader(reader); return nullptr; } const auto& m = reader->GetVariableToDataTypeMap(); for (auto it = m.begin(); it != m.end(); ++it) reader->variable_list.push_back(it->first); std::sort(reader->variable_list.begin(), reader->variable_list.end()); return reader; }
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 03:35:10 GMT 2024 - 29.4K bytes - Viewed (0) -
.github/workflows/update-rbe.yml
# The "digest" that allows us to pull an image is not the digest as # returned by the API, but a sha256sum of the entire chunk of image # metadata. gcr.io helpfully includes it in the header of the response # as docker-content-digest: sha256:[digest]. Note we use egrep to # match exactly sha256:<hash> because curl may include a ^M symbol at # the end of the line.
Others - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Wed Apr 10 15:40:34 GMT 2024 - 7.2K bytes - Viewed (0) -
.bazelrc
# nothing in a bazelrc will default to a monolithic build. The following line # opts in to modular op registration support by default. build --define framework_shared_object=true build --define tsl_protobuf_header_only=true build --define=use_fast_cpp_protos=true build --define=allow_oversize_protos=true build --spawn_strategy=standalone build -c opt # Make Bazel print out all options from rc files.
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tensorflow/c/eager/BUILD
"//tensorflow/core/common_runtime/eager:attr_builder", "//tensorflow/core/common_runtime/eager:context", "//tensorflow/core/common_runtime/eager:copy_to_device_node", "//tensorflow/core/common_runtime/eager:eager_executor", "//tensorflow/core/common_runtime/eager:eager_operation", "//tensorflow/core/common_runtime/eager:execute",
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tensorflow/BUILD
# cc_shared_library to work. "//tensorflow/c/eager:c_api_experimental", "//tensorflow/c/eager:c_api_internal", "//tensorflow/c/eager:dlpack", "//tensorflow/c/eager:tape", "//tensorflow/c/eager:tfe_context_internal", "//tensorflow/c/eager:tfe_op_internal", "//tensorflow/c/eager:tfe_tensorhandle_internal", "//tensorflow/c/experimental/gradients",
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RELEASE.md
based server to register tf.function methods and a GRPC client to invoke remote registered methods. RPC APIs are intended for multi-client setups i.e. server and clients are started in separate binaries independently. * Example usage to create server: ```python server = tf.distribute.experimental.rpc.Server.create("grpc", "127.0.0.1:1234")
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